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In-depth research and data-driven insights on quantitative finance, factor investing, risk, and ESG from the TEJ research team.
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Fundamental Factor Research: Monthly Revenue Information – part1
The Taiwan equity market possesses a rare institutional advantage globally: under the Securities and Exchange Act, listed companies are required to announce and report their operational results for the preceding month by the 10th of each month (Exception: starting from FY2026, insurance companies and entities with insurance subsidiaries may extend their disclosure deadline to the 15th of each month). This is commonly referred to in the market as "Monthly Revenue".
Factor Research – Tracking Smart Money Footprints via Foreign Institutional Concentration – QFII Part 1
Track QFII ‘smart money’ footprints in Taiwan large-cap stocks! Learn how the Foreign-Institutional Trading Concentration (conc_qfii) factor predicts returns.
Empirical Research on Behavioral Factors in the Taiwan Stock Market: A Case Study of the Share Distribution
In an AI-driven Taiwan stock market, mastering chip distribution (ownership structure) is the key to profitability. This study delves into the Share Distribution data from the TDCC, transforming 15 tiers of shareholding data into behavioral finance factors such as investor attention, opinion dispersion, and retail speculation. By utilizing Fama–MacBeth two-stage regression and the alphalens-tej quantitative tool, we precisely validate the predictive power of psychological biases on stock returns, providing investors with actionable Alpha strategies and robust risk management solutions.
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Factor Investing
Empirical Study on Behavioral Factors in the Taiwan Stock Market: An Analysis of Broker Branch Trading Factors (Part 2)
In the previous study, we verified the fundamental chip-analysis principle of "institutional/major players going momentum, retail investors going contrarian" in the Taiwan stock market, and identified the "Major Player Net Buying Strength (by Amount)" factor, which exhibited the highest winning rate and most stable performance. In this second part, we conduct backtests to evaluate the actual profitability of this major player factor across different holding periods, while analyzing how transaction fees and turnover rates impact final trading performance.
Factor Investing
Empirical Study on Behavioral Factors in the Taiwan Stock Market: An Analysis of Broker Branch Trading Factors (Part 1)
The Taiwan stock market is renowned for its high retail investor participation and exceptional market transparency. Every day after the market close, the Taiwan Stock Exchange (TWSE) and the Taipei Exchange (TPEx) publish detailed Broker Branch Trading Database. This dataset itemizes the exact buy and sell volume and transaction values executed by every brokerage branch across all listed equities. Compared with centralized depository shareholder distribution reports published weekly, brokerage branch data offers daily frequency, clear identification of market entities, and trade directionality. These features make it the premier tool for investors analyzing market participant positioning. However, many investors who trade based on branch flow fall into the trap of buying at market tops. Behavioral finance demonstrates that information asymmetries and psychological biases directly manifest in trading behaviors. On one hand, institutional investors and large accounts with genuine information advantages (smart money) execute sizable, concentrated orders, driving subsequent price momentum. On the other hand, when a stock gains widespread retail attention, excessive retail buying often drives crowd sentiment and asset congestion, causing prices to temporarily detach from fundamental value before undergoing mean reversion.
Factor Investing
Factor Research – Tracking Smart Money Footprints via Foreign Institutional Concentration – QFII Part 1
Track QFII ‘smart money’ footprints in Taiwan large-cap stocks! Learn how the Foreign-Institutional Trading Concentration (conc_qfii) factor predicts returns.
Factor Investing
Factor Strategy – Integrating Broker Consensus to Enhance Foreign Concentration Strategies – QFII Part 2
Boost your quantitative strategy with QFII concentration & broker consensus! Discover how the conc_qfii fusion strategy delivers a 30.12% annualized return in the Taiwan large-cap market.
Factor Investing
Empirical Research on Behavioral Factors in the Taiwan Stock Market: A Case Study of the Share Distribution
In an AI-driven Taiwan stock market, mastering chip distribution (ownership structure) is the key to profitability. This study delves into the Share Distribution data from the TDCC, transforming 15 tiers of shareholding data into behavioral finance factors such as investor attention, opinion dispersion, and retail speculation. By utilizing Fama–MacBeth two-stage regression and the alphalens-tej quantitative tool, we precisely validate the predictive power of psychological biases on stock returns, providing investors with actionable Alpha strategies and robust risk management solutions.
Factor Investing
Factor Strategy – Applying SIR to Strengthen Momentum Strategies in the Taiwan Market – SIR Part 2
This study examines whether incorporating the Short Interest Ratio (SIR) can improve the performance of a 52-week high momentum strategy in Taiwan. By comparing a baseline momentum model with two SIR-enhanced versions—one using SIR as a filter and another integrating it into a composite score—we find consistent gains in returns, lower volatility, and reduced drawdowns. The results show that SIR strengthens momentum strategies by identifying stocks under institutional short-selling pressure.
Factor Investing
Factor Research – The SIR Short-Selling Factor: Extracting Negative Signals from Institutional Borrowing Activity – SIR Part 1
Taiwan’s short-selling signals are often misleading because the market operates under a dual-track system: retail investors short stocks through margin accounts, while institutional investors use securities borrowing and lending (SBL). Only SBL-based short selling reflects informed institutional sentiment, while margin shorting introduces noise. This study isolates SBL to construct the Short Interest Ratio (SIR) and evaluates its ability to predict cross-sectional returns and reveal size-dependent patterns in informed short-selling behavior.
Factor Investing
Discovering Investment Factors through Point-in-Time Audited Financial Database
This study employs TEJ’s Point-in-Time Audited Financial Database to construct a composite factor for stock selection in Taiwan’s equity market. By preserving financial data exactly as available at each historical moment, the framework avoids look-ahead bias and ensures empirical reliability. We find that higher-ranked portfolios deliver significant short-term excess returns, while predictive power weakens over longer horizons. The results highlight the practical value of Point-in-Time financial data for quantitative factor investing and underscore its role in building replicable, data-driven investment strategies.
Factor Investing
Jabli–Watson Factor Model: The Growth Formula for Quantitative Momentum Investing
Gabriel Watson is a well-known American growth-momentum portfolio manager. In his early career, he worked at Morgan Stanley Investment Management and William O’Neil & Co., where he accumulated extensive market research experience. Since joining Black Rose Capital Management in 1998, Watson has broken away from the confines of traditional value investing and developed a systematic, rule-based stock-picking method centered on “revenue momentum and price strength.” He calls this framework “The Machine.” In an environment characterized by rapid information flow and swift capital rotation, this approach has enabled him to capture the powerful upward moves of leading stocks.
Factor Investing
Factor Investing Explained: Types of Factors & Strategy Guide
Factor investing targets quantifiable characteristics to improve returns. Explores common factors (macroeconomic and style types) and strategies in our guide.
Factor Investing
Factor Strategy – Capital Gain Overhang | Part 2
In the previous study, we examined the Capital Gain Overhang (CGO) factor, designed to capture the behavioral bias known as the Disposition Effect. By measuring the gap between current market prices and investors’ average cost basis, CGO quantifies unrealized gains and losses at the market level. Empirical tests in Taiwan’s equity market confirmed that CGO is a meaningful predictor of future returns: high-CGO stocks consistently outperformed low-CGO stocks, generating significant positive alpha beyond standard Fama–French models, especially over medium- to long-term horizons.
Factor Investing
Factor Research –Capital Gain Overhang | Part 1
The origins of the momentum anomaly have long been debated, with multiple competing explanations. Among them, one of the most influential behavioral interpretations attributes momentum to the Disposition Effect, a systematic bias in investor decision-making. This article focuses on the Capital Gain Overhang (CGO) factor, specifically designed to quantify this behavioral bias. Using the Taiwan equity market as a case study, we examine CGO’s predictive power as a stock selection indicator and evaluate its practical value through empirical analysis.